改进Retinex的光照变化人脸图像增强算法  

Face Enhancement Algorithm with Variable Illumination Based on Improved Retinex

作　　者：杜明[1] 赵向军[1] 

机构地区：[1]江苏师范大学计算机科学与技术学院,徐州221116

出　　处：《计算机科学》2016年第2期105-108,112,共5页Computer Science

基　　金：国家自然科学基金(61272297);江苏师范大学自然科学基金(13XLB03)资助

摘　　要：为了提高可变光照条件下的人脸图像整体效果,提出一种基于改进单尺度Retinex的光照变化人脸增强算法。首先对人脸图像进行对数变换,经过曲波变换得到高频和低频两部分;然后采用双边滤波对高频进行去噪处理,同时采用Kimmel变分模型对低频部分进行光滑滤波;最后对人脸图像进行重构,并对图像进行伽马校正处理。在Yale B光照人脸库上的实验结果表明,该算法能较好地防止"光晕"现象出现,可以还原出人脸图像的本来面貌,使人脸图像更加适合人眼观察。In order to improve the overall effect of face images with variable illumination,this paper proposed a novel face enhancement algorithm with variable illumination based on single scale Retinex.Firstly,the face images are logarithmically transformed,and the image is transformed into frequency and low frequency part by curvelet transform.Secondly,the bilateral filtering is used to denoise the high frequency while Kimmel variation model is used to smooth filtering low frequency part.Finally,the image is reconstructed,and Gamma is used to correct the image.The experimental results on Yale B database show that the proposed algorithm can prevent the＂halos＂phenomenon,and can restore the original face image,so the face image is more suitable for human eye observation.

关 键 词：人脸识别 可变光照 图像增强 色彩恒常理论 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]